As high-definition display devices rapidly develop, demands on high-resolution images and videos are increasing. At the present stage, a low-resolution image may be converted into a high-resolution image by various methods, for example, a differential-based method, a reconstruction-based method, and a learning-based method. However, when a series of operations are performed on an image to convert the image from a low-resolution image to a high-resolution image, image distortion is often caused, so that the image is unable to meet actual requirements. For example, after a low-resolution facial image is converted into a high-resolution facial image through a series of operations, the face is distorted and cannot be correctly recognized. Therefore, when the low-resolution image is converted into the high-resolution image, how to avoid the image distortion as much as possible and ensure the authenticity of the image is an urgent problem to be solved.